• DocumentCode
    678726
  • Title

    Finding a vine´s structure by bottom-up parsing of cane edges

  • Author

    Botterill, Tom ; Green, Ron ; Mills, Steven

  • Author_Institution
    Dept. of Comput. Sci., Univ. of Canterbury, Christchurch, New Zealand
  • fYear
    2013
  • fDate
    27-29 Nov. 2013
  • Firstpage
    112
  • Lastpage
    117
  • Abstract
    A vine pruning robot uses stereo cameras to build a 3D model of vines. The robot´s 3D reconstruction scheme requires the 2D structure of the vine to be extracted from each image. This paper describes how the 2D structure is extracted. We propose an image grammar-based model for how a vine generates an image. We extract cane edges from each image, then apply a bottom-up parse of the cane edges to find a vine structure explaining the image. The method is efficient and accurate, and the 2D structures are complete enough that complete 3D models of vines can be reconstructed. The scheme demonstrates the power of the image grammar model for solving complex image interpretation problems.
  • Keywords
    edge detection; feature extraction; grammars; image reconstruction; image sensors; image thinning; robot vision; solid modelling; stereo image processing; 3D reconstruction scheme; bottom-up cane edge parsing; complex image interpretation problems; image grammar-based model; skeletonisation algorithms; stereo cameras; vine 2D structure extraction; vine 3D model; vine pruning robot; vine structure; Computational modeling; Grammar; Image edge detection; Image segmentation; Robots; Solid modeling; Three-dimensional displays;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Image and Vision Computing New Zealand (IVCNZ), 2013 28th International Conference of
  • Conference_Location
    Wellington
  • ISSN
    2151-2191
  • Print_ISBN
    978-1-4799-0882-0
  • Type

    conf

  • DOI
    10.1109/IVCNZ.2013.6727001
  • Filename
    6727001